Image Interpolation Algorithm for Edge Detection Using Directional Filters and Data Fusion

Preserving edge structures is a challenge to the image interpolation algorithms to reconstruct a high resolution image from a low resolution counterpart. We propose a new guide edge linear interpolation technique via address filter and data fusion. For a pixel to be interpolated, two sets of observation are defined in two orthogonal directions, and each set produces an estimated value of the pixel. These estimates of direction, following the model the different measures of the lack of noisy pixels are fused by linear least mean square estimation error (LMMSE) technique in a more robust estimate, and statistics two sets of observations. It also presents a simplified version of Based LMMSE interpolation algorithm to reduce computational cost without sacrificing much the interpolation performance. Experiments show that the new interpolation techniques can preserve sharp edges and reduce artifacts call.